Finance Data Engineer

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Company Overview

A leading global technology organization is seeking a Finance Data Engineer to support the development of innovative data products within its finance function. The company leverages enterprise-scale data warehouse and lakehouse environments to drive business insights, enable advanced analytics, and support emerging AI and machine learning initiatives. This role offers the opportunity to collaborate with cross-functional teams to build scalable, reliable, and high-quality data solutions that support critical business operations.

The Finance Data Engineer is a technical expert responsible for designing and building data interfaces, pipelines, and codebases that power finance data products. This role focuses on delivering reliable, accurate, consistent, and architecturally sound solutions aligned with business requirements.

The successful candidate will work closely with business users, data scientists, machine learning engineers, software engineers, and technology teams to develop and deploy data services and pipelines. A strong understanding of data engineering principles and the ability to learn finance business processes are essential for success in this position.

Key Responsibilities

• Partner with data scientists, machine learning engineers, software engineers, and business stakeholders to identify, capture, collect, load, and format data from internal systems, external sources, and enterprise data warehouses.
• Develop, test, deploy, monitor, document, and troubleshoot data pipelines and feature-ready datasets.
• Collaborate with engineering teams to establish and adopt best practices for translating finance use cases into data requirements, schemas, and retrieval patterns for RAG, AI agents, and other large language model workflows.
• Evaluate emerging technologies and identify opportunities to adopt innovative tools, techniques, and platforms.
• Build scalable data solutions within enterprise data warehouse and lakehouse environments.
• Ensure data reliability, consistency, quality, and performance across data products and services.
• Support data integration and automation initiatives to improve business decision-making capabilities.

Required Qualifications

• 5+ years of relevant Data Engineering experience.
• Bachelor’s degree in Computer Science, MIS, Engineering, Mathematics, or another quantitative discipline.
• Strong proficiency in Python, Shell scripting, and SQL.
• Hands-on experience with database design and architecture in cloud data warehouse environments such as Snowflake and lakehouse environments utilizing Amazon S3.
• Experience implementing end-to-end encryption and decryption policies for sensitive data pipelines, semantic views, and related data sources.
• Strong understanding of the data development lifecycle, including CI/CD processes and version control tools such as Jenkins and Git.
• Experience with cloud platforms and orchestration technologies, including AWS and Kubernetes.
• Knowledge of streaming interfaces and data pipeline architectures.
• Experience building data and automation services through RESTful APIs.
• Strong focus on data quality, validation, and governance across all pipelines.
• Finance and accounting process knowledge is considered an advantage.

Disclaimer

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